Category: sociology

Pathogen Resistance


Alt/title text:

We’re not not trapped in here with the coronavirus. The coronavirus is trapped in here with us.

Explain xkcd

How Soon Will COVID-19 Peak?

Difficult to tell, but the sooner social distancing is applied the better. Stay at home.

Bullshitters. Who Are They and What Do We Know about Their Lives?

John Jerrim, Phil Parker, Nikki Shure

‘Bullshitters’ are individuals who claim knowledge or expertise in an area where they actually have little experience or skill. Despite this being a well-known and widespread social phenomenon, relatively few large-scale empirical studies have been conducted into this issue. This paper attempts to fill this gap in the literature by examining teenagers’ propensity to claim expertise in three mathematics constructs that do not really exist. Using Programme for International Student Assessment (PISA) data from nine Anglophone countries and over 40,000 young people, we find substantial differences in young people’s tendency to bullshit across countries, genders and socio-economic groups. Bullshitters are also found to exhibit high levels of overconfidence and believe they work hard, persevere at tasks, and are popular amongst their peers. Together this provides important new insight into who bullshitters are and the type of survey responses that they provide.

IZA – Institute of Labor Economics (PDF)

Image credit: Roy Lichtenstein, “Cow Triptych / Cow Going Abstract”


Daily Nous: 

An Empirical Study of Bullshitters

Sister Rosetta Tharpe

All this new stuff they call rock ’n’ roll, why, I’ve been playing that for years now… Ninety percent of rock-and-roll artists came out of the church, their foundation is the church.

A hipster queen among hipsters, she was already empowering herself (doubly) even before the very word was created. Love.

[Impressed with the amount of legitimate tags that I can use in this post to be this (more or less) a science blog]

Happy World Emoji Day!


Image from this article: The psychology of emojis

Why and how twitter did change the characters limit, a perfect example of data science at work: data acquisition, data filtering and cleaning, modeling and validation, analysis, conclusions and inference.

Also interesting the design implementation:

For my part, I like the update and think is a improvement, especially when you realize that it is not mandatory to use 240 characters (neither were 140), I think keeping Twitter’s brevity is still a good policy, as suggested in the announcement blogpost:

“We – and many of you – were concerned that timelines may fill up with 280 character Tweets, and people with the new limit would always use up the whole space. But that didn’t happen. Only 5% of Tweets sent were longer than 140 characters and only 2% were over 190 characters. As a result, your timeline reading experience should not substantially change, you’ll still see about the same amount of Tweets in your timeline.“